为研究不同养殖方式下宁都黄鸡肌肉关键挥发性风味物质,将试验鸡随机分为笼养组和平养组,饲喂同一日粮。试验鸡达上市日龄时对鸡肉进行感官品尝评价和挥发性风味物质检测,并采用正交偏最小二乘-判别分析(orthogonal partial least squar...为研究不同养殖方式下宁都黄鸡肌肉关键挥发性风味物质,将试验鸡随机分为笼养组和平养组,饲喂同一日粮。试验鸡达上市日龄时对鸡肉进行感官品尝评价和挥发性风味物质检测,并采用正交偏最小二乘-判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA)方法筛选与不同养殖方式相关的差异性风味物质。结果表明:平养组和笼养组共有的挥发性风味物质27种,主要为酚类、醇类和烃类。挥发性风味物质中,己醛、1-辛烯-3-醇、E-2-壬烯醛、正己醇、壬醛、2,3-戊二酮、癸醛、2,3-辛二酮、E-2-辛烯醛为具有显著性差异的挥发性风味物质。综上,这一研究可为地方鸡肉品质基于风味物质的评价提供科学依据。展开更多
Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currentl...Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.展开更多
目的:以牛磺熊去氧胆酸和牛磺鹅去氧胆酸为指标,建立龙泽熊胆胶囊中熊胆粉的含量测定方法。方法:采用高效液相色谱串联蒸发光检测器,色谱柱为ChromCore AQ C 18(4.6 mm×250 mm,5μm),乙腈(A)-5 mmol•L^(-1)醋酸铵溶液(B)为流动相,...目的:以牛磺熊去氧胆酸和牛磺鹅去氧胆酸为指标,建立龙泽熊胆胶囊中熊胆粉的含量测定方法。方法:采用高效液相色谱串联蒸发光检测器,色谱柱为ChromCore AQ C 18(4.6 mm×250 mm,5μm),乙腈(A)-5 mmol•L^(-1)醋酸铵溶液(B)为流动相,梯度洗脱(0~40 min,25%A;40~50 min,25%A→29%A;50~80 min,29%A;80~100 min,29%A→40%A),流速1.0 mL•min^(-1),柱温30℃,ELSD漂移管温度110℃,氮流量2.5L•min^(-1)。结果:牛磺熊去氧胆酸进样量在1.069~9.57μg内、牛磺鹅去氧胆酸进样量在0.74046~7.40464μg内,进样量的对数与峰面积的对数呈良好的线性关系;仪器精密度、重复性、稳定性试验的RSD<2.0%;经低、中、高3个浓度的准确度试验考察,牛磺熊去氧胆酸的回收率为95.2%~97.7%,牛磺鹅去氧胆酸的回收率为91.9%~95.9%。测定样品42批次,牛磺熊去氧胆酸和牛磺鹅去氧胆酸的含量分别为0.18~0.43、0.10~0.44 mg•粒^(-1)。结论:本法适用于龙泽熊胆胶囊中熊胆粉的质量控制,可为完善龙泽熊胆胶囊的质量标准提供科学的依据。展开更多
Accurate ultra-short-term prediction of the Earth rotation parameters(ERP)holds paramount impor-tance for real-time applications,particularly in reference frame conversion.Among them,diurnal rota-tion(UT1-UTC)which ca...Accurate ultra-short-term prediction of the Earth rotation parameters(ERP)holds paramount impor-tance for real-time applications,particularly in reference frame conversion.Among them,diurnal rota-tion(UT1-UTC)which cannot be directly estimated through Global Navigation Satellite System(GNSS)techniques,significantly affects the rapid and ultra-rapid orbit determination of GNsS satellites.Pres-ently,the traditional LS(least squares)+AR(autoregressive)and LS+MAR(multivariate autoregressive)hybrid methods stand as primary approaches for UT1-UTC ultra-short-term predictions(1-10 days).The LS+MAR hybrid method relies on the UT1-UTC and LOD(length of day)series.However,the correlation between LOD and first-order-difference UT1-UTC is stronger than that between LOD and UT1-UTC.In light of this,and with the aid of the first-order-difference UT1-UTC,we propose an enhanced LS+MAR hybrid method to UT1-UTC ultra-short-term prediction.By using the UT1-UTC and LOD data series of the IERS(International Earth Rotation and Reference Systems Service)EOP 14 C04 product,we conducted a thorough analysis and evaluation of the improved method's prediction performance compared to the traditional LS+AR and LS+MAR hybrid methods.According to the numerical results over more than 210 days,they demonstrate that,when considering the correlation information between the LoD and the first-order-difference UT1-UTC,the mean absolute errors(MAEs)of the improved LS+MAR hybrid method range from 21 to 934μs in 1-10 days predictions.In comparison to the traditional LS+AR hybrid method,the MAEs show a reduction of 7-53μs in 1-10 days predictions,with corresponding improvement percentages ranging from 1 to 28%.Similarly,when compared to the traditional LS+MAR hybrid method,the MAEs have a reduction of 5-42μs in 1-10 days predictions,with corresponding improvement percentages ranging from 4-20%.Additionally,when aided by GNSS-derived LOD data series,the MAEs of improved LS+MAR hybrid method experience further reduction.展开更多
针对传统矿浆细度检测的离线筛分法效率低且不能及时反馈至上层磨矿系统的问题,为开发出细度自动检测技术,提出一种曲面拟合算法,即:基于最小二乘法改进的移动最小截平方法(MLTS-LS,Moving Least Trimmed Square-Least Square)对矿浆细...针对传统矿浆细度检测的离线筛分法效率低且不能及时反馈至上层磨矿系统的问题,为开发出细度自动检测技术,提出一种曲面拟合算法,即:基于最小二乘法改进的移动最小截平方法(MLTS-LS,Moving Least Trimmed Square-Least Square)对矿浆细度数据进行曲面拟合,以达到快速检测矿浆细度的目的。首先,通过细度检测试验采集矿浆细度三维离散数据;其次,计算分析“Nearest”、“Linear”、“Cubic”、“V4”和传统的最小二乘法的曲面拟合评价指标,提出一种改进的插值算法;最后,将“MLTS-LS”算法应用于矿浆细度三维离散数据的拟合。结果显示,“MLTS-LS”算法的和方差值与均方差值明显小于其他算法,且其确定系数值与校正决定系数值均接近于1,表明“MLTS-LS”算法对矿浆细度三维离散数据的拟合效果较好。展开更多
文摘为研究不同养殖方式下宁都黄鸡肌肉关键挥发性风味物质,将试验鸡随机分为笼养组和平养组,饲喂同一日粮。试验鸡达上市日龄时对鸡肉进行感官品尝评价和挥发性风味物质检测,并采用正交偏最小二乘-判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA)方法筛选与不同养殖方式相关的差异性风味物质。结果表明:平养组和笼养组共有的挥发性风味物质27种,主要为酚类、醇类和烃类。挥发性风味物质中,己醛、1-辛烯-3-醇、E-2-壬烯醛、正己醇、壬醛、2,3-戊二酮、癸醛、2,3-辛二酮、E-2-辛烯醛为具有显著性差异的挥发性风味物质。综上,这一研究可为地方鸡肉品质基于风味物质的评价提供科学依据。
基金supported by National Natural Science Foundation of China,China(No.42004016)HuBei Natural Science Fund,China(No.2020CFB329)+1 种基金HuNan Natural Science Fund,China(No.2023JJ60559,2023JJ60560)the State Key Laboratory of Geodesy and Earth’s Dynamics self-deployment project,China(No.S21L6101)。
文摘Short-term(up to 30 days)predictions of Earth Rotation Parameters(ERPs)such as Polar Motion(PM:PMX and PMY)play an essential role in real-time applications related to high-precision reference frame conversion.Currently,least squares(LS)+auto-regressive(AR)hybrid method is one of the main techniques of PM prediction.Besides,the weighted LS+AR hybrid method performs well for PM short-term prediction.However,the corresponding covariance information of LS fitting residuals deserves further exploration in the AR model.In this study,we have derived a modified stochastic model for the LS+AR hybrid method,namely the weighted LS+weighted AR hybrid method.By using the PM data products of IERS EOP 14 C04,the numerical results indicate that for PM short-term forecasting,the proposed weighted LS+weighted AR hybrid method shows an advantage over both the LS+AR hybrid method and the weighted LS+AR hybrid method.Compared to the mean absolute errors(MAEs)of PMX/PMY sho rt-term prediction of the LS+AR hybrid method and the weighted LS+AR hybrid method,the weighted LS+weighted AR hybrid method shows average improvements of 6.61%/12.08%and 0.24%/11.65%,respectively.Besides,for the slopes of the linear regression lines fitted to the errors of each method,the growth of the prediction error of the proposed method is slower than that of the other two methods.
基金supported by China Natural Science Fund,China(No.42004016)the science and technology innovation Program of Hunan Province,China(No.2023RC3217)+1 种基金Research Foundation of the Department of Natural Resources of Hunan Province(Grant No:20240105CH)HuBei Natural Science Fund,China(No.2020CFB329).
文摘Accurate ultra-short-term prediction of the Earth rotation parameters(ERP)holds paramount impor-tance for real-time applications,particularly in reference frame conversion.Among them,diurnal rota-tion(UT1-UTC)which cannot be directly estimated through Global Navigation Satellite System(GNSS)techniques,significantly affects the rapid and ultra-rapid orbit determination of GNsS satellites.Pres-ently,the traditional LS(least squares)+AR(autoregressive)and LS+MAR(multivariate autoregressive)hybrid methods stand as primary approaches for UT1-UTC ultra-short-term predictions(1-10 days).The LS+MAR hybrid method relies on the UT1-UTC and LOD(length of day)series.However,the correlation between LOD and first-order-difference UT1-UTC is stronger than that between LOD and UT1-UTC.In light of this,and with the aid of the first-order-difference UT1-UTC,we propose an enhanced LS+MAR hybrid method to UT1-UTC ultra-short-term prediction.By using the UT1-UTC and LOD data series of the IERS(International Earth Rotation and Reference Systems Service)EOP 14 C04 product,we conducted a thorough analysis and evaluation of the improved method's prediction performance compared to the traditional LS+AR and LS+MAR hybrid methods.According to the numerical results over more than 210 days,they demonstrate that,when considering the correlation information between the LoD and the first-order-difference UT1-UTC,the mean absolute errors(MAEs)of the improved LS+MAR hybrid method range from 21 to 934μs in 1-10 days predictions.In comparison to the traditional LS+AR hybrid method,the MAEs show a reduction of 7-53μs in 1-10 days predictions,with corresponding improvement percentages ranging from 1 to 28%.Similarly,when compared to the traditional LS+MAR hybrid method,the MAEs have a reduction of 5-42μs in 1-10 days predictions,with corresponding improvement percentages ranging from 4-20%.Additionally,when aided by GNSS-derived LOD data series,the MAEs of improved LS+MAR hybrid method experience further reduction.
文摘针对传统矿浆细度检测的离线筛分法效率低且不能及时反馈至上层磨矿系统的问题,为开发出细度自动检测技术,提出一种曲面拟合算法,即:基于最小二乘法改进的移动最小截平方法(MLTS-LS,Moving Least Trimmed Square-Least Square)对矿浆细度数据进行曲面拟合,以达到快速检测矿浆细度的目的。首先,通过细度检测试验采集矿浆细度三维离散数据;其次,计算分析“Nearest”、“Linear”、“Cubic”、“V4”和传统的最小二乘法的曲面拟合评价指标,提出一种改进的插值算法;最后,将“MLTS-LS”算法应用于矿浆细度三维离散数据的拟合。结果显示,“MLTS-LS”算法的和方差值与均方差值明显小于其他算法,且其确定系数值与校正决定系数值均接近于1,表明“MLTS-LS”算法对矿浆细度三维离散数据的拟合效果较好。
